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<li><a class="reference internal" href="#">pymatgen.analysis.structure_prediction package</a><ul>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-pymatgen.analysis.structure_prediction.dopant_predictor">pymatgen.analysis.structure_prediction.dopant_predictor module</a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.dopant_predictor.get_dopants_from_shannon_radii"><code class="docutils literal notranslate"><span class="pre">get_dopants_from_shannon_radii()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.dopant_predictor.get_dopants_from_substitution_probabilities"><code class="docutils literal notranslate"><span class="pre">get_dopants_from_substitution_probabilities()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-pymatgen.analysis.structure_prediction.substitution_probability">pymatgen.analysis.structure_prediction.substitution_probability module</a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor"><code class="docutils literal notranslate"><span class="pre">SubstitutionPredictor</span></code></a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor.composition_prediction"><code class="docutils literal notranslate"><span class="pre">SubstitutionPredictor.composition_prediction()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor.list_prediction"><code class="docutils literal notranslate"><span class="pre">SubstitutionPredictor.list_prediction()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability</span></code></a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.as_dict"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.as_dict()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.cond_prob"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.cond_prob()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.cond_prob_list"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.cond_prob_list()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.from_dict"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.from_dict()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.get_lambda"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.get_lambda()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.get_px"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.get_px()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.pair_corr"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.pair_corr()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.prob"><code class="docutils literal notranslate"><span class="pre">SubstitutionProbability.prob()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#module-pymatgen.analysis.structure_prediction.substitutor">pymatgen.analysis.structure_prediction.substitutor module</a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor"><code class="docutils literal notranslate"><span class="pre">Substitutor</span></code></a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.as_dict"><code class="docutils literal notranslate"><span class="pre">Substitutor.as_dict()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.charge_balanced_tol"><code class="docutils literal notranslate"><span class="pre">Substitutor.charge_balanced_tol</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.from_dict"><code class="docutils literal notranslate"><span class="pre">Substitutor.from_dict()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.get_allowed_species"><code class="docutils literal notranslate"><span class="pre">Substitutor.get_allowed_species()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_comp"><code class="docutils literal notranslate"><span class="pre">Substitutor.pred_from_comp()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_list"><code class="docutils literal notranslate"><span class="pre">Substitutor.pred_from_list()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_structures"><code class="docutils literal notranslate"><span class="pre">Substitutor.pred_from_structures()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#module-pymatgen.analysis.structure_prediction.volume_predictor">pymatgen.analysis.structure_prediction.volume_predictor module</a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor"><code class="docutils literal notranslate"><span class="pre">DLSVolumePredictor</span></code></a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor.get_predicted_structure"><code class="docutils literal notranslate"><span class="pre">DLSVolumePredictor.get_predicted_structure()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor.predict"><code class="docutils literal notranslate"><span class="pre">DLSVolumePredictor.predict()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor"><code class="docutils literal notranslate"><span class="pre">RLSVolumePredictor</span></code></a><ul>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor.get_predicted_structure"><code class="docutils literal notranslate"><span class="pre">RLSVolumePredictor.get_predicted_structure()</span></code></a></li>
<li><a class="reference internal" href="#pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor.predict"><code class="docutils literal notranslate"><span class="pre">RLSVolumePredictor.predict()</span></code></a></li>
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</li>
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</li>
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  <section id="module-pymatgen.analysis.structure_prediction">
<span id="pymatgen-analysis-structure-prediction-package"></span><h1>pymatgen.analysis.structure_prediction package<a class="headerlink" href="#module-pymatgen.analysis.structure_prediction" title="Link to this heading"></a></h1>
<p>Utilities to predict new structures.</p>
<section id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading"></a></h2>
</section>
<section id="module-pymatgen.analysis.structure_prediction.dopant_predictor">
<span id="pymatgen-analysis-structure-prediction-dopant-predictor-module"></span><h2>pymatgen.analysis.structure_prediction.dopant_predictor module<a class="headerlink" href="#module-pymatgen.analysis.structure_prediction.dopant_predictor" title="Link to this heading"></a></h2>
<p>Predicting potential dopants.</p>
<dl class="py function">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.dopant_predictor.get_dopants_from_shannon_radii">
<span class="sig-name descname"><span class="pre">get_dopants_from_shannon_radii</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bonded_structure</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_dopants</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">match_oxi_sign</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/dopant_predictor.py#L60-L125"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.dopant_predictor.get_dopants_from_shannon_radii" title="Link to this definition"></a></dt>
<dd><p>Get dopant suggestions based on Shannon radii differences.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bonded_structure</strong> (<a class="reference internal" href="pymatgen.analysis.html#pymatgen.analysis.graphs.StructureGraph" title="pymatgen.analysis.graphs.StructureGraph"><em>StructureGraph</em></a>) – A pymatgen structure graph
decorated with oxidation states. For example, generated using the
CrystalNN.get_bonded_structure() method.</p></li>
<li><p><strong>num_dopants</strong> (<em>int</em>) – The number of suggestions to return for
n- and p-type dopants.</p></li>
<li><p><strong>match_oxi_sign</strong> (<em>bool</em>) – Whether to force the dopant and original species
to have the same sign of oxidation state. E.g. If the original site
is in a negative charge state, then only negative dopants will be
returned.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>Dopant suggestions, given as a dictionary with keys “n_type” and</dt><dd><p>”p_type”. The suggestions for each doping type are given as a list of
dictionaries, each with they keys:</p>
<ul class="simple">
<li><p>”radii_diff”: The difference between the Shannon radii of the species.</p></li>
<li><p>”dopant_species”: The dopant species.</p></li>
<li><p>”original_species”: The substituted species.</p></li>
</ul>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>dict</p>
</dd>
</dl>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.dopant_predictor.get_dopants_from_substitution_probabilities">
<span class="sig-name descname"><span class="pre">get_dopants_from_substitution_probabilities</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_dopants</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">match_oxi_sign</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/dopant_predictor.py#L13-L57"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.dopant_predictor.get_dopants_from_substitution_probabilities" title="Link to this definition"></a></dt>
<dd><p>Get dopant suggestions based on substitution probabilities.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – A pymatgen structure decorated with
oxidation states.</p></li>
<li><p><strong>num_dopants</strong> (<em>int</em>) – The number of suggestions to return for
n- and p-type dopants.</p></li>
<li><p><strong>threshold</strong> (<em>float</em>) – Probability threshold for substitutions.</p></li>
<li><p><strong>match_oxi_sign</strong> (<em>bool</em>) – Whether to force the dopant and original species
to have the same sign of oxidation state. E.g. If the original site
is in a negative charge state, then only negative dopants will be
returned.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>Dopant suggestions, given as a dictionary with keys “n_type” and</dt><dd><p>”p_type”. The suggestions for each doping type are given as a list of
dictionaries, each with they keys:</p>
<ul class="simple">
<li><p>”probability”: The probability of substitution.</p></li>
<li><p>”dopant_species”: The dopant species.</p></li>
<li><p>”original_species”: The substituted species.</p></li>
</ul>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>dict</p>
</dd>
</dl>
</dd></dl>

</section>
<section id="module-pymatgen.analysis.structure_prediction.substitution_probability">
<span id="pymatgen-analysis-structure-prediction-substitution-probability-module"></span><h2>pymatgen.analysis.structure_prediction.substitution_probability module<a class="headerlink" href="#module-pymatgen.analysis.structure_prediction.substitution_probability" title="Link to this heading"></a></h2>
<p>This module provides classes for representing species substitution probabilities.</p>
<dl class="py class">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor">
<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">SubstitutionPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lambda_table</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L184-L281"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Predicts likely substitutions either to or from a given composition
or species list using the SubstitutionProbability.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>lambda_table</strong> (<em>dict</em>) – Input lambda table.</p></li>
<li><p><strong>alpha</strong> (<em>float</em>) – weight function for never observed substitutions</p></li>
<li><p><strong>threshold</strong> (<em>float</em>) – Threshold to use to identify high probability structures.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor.composition_prediction">
<span class="sig-name descname"><span class="pre">composition_prediction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">composition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_this_composition</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L252-L281"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor.composition_prediction" title="Link to this definition"></a></dt>
<dd><p>Get charged balanced substitutions from a starting or ending
composition.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>composition</strong> – starting or ending composition</p></li>
<li><p><strong>to_this_composition</strong> – If true, substitutions with this as a final composition
will be found. If false, substitutions with this as a
starting composition will be found (these are slightly
different)</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>List of predictions in the form of dictionaries.
If to_this_composition is true, the values of the dictionary
will be from the list species. If false, the keys will be
from that list.</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor.list_prediction">
<span class="sig-name descname"><span class="pre">list_prediction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">species</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_this_composition</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L200-L250"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionPredictor.list_prediction" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>species</strong> – list of species</p></li>
<li><p><strong>to_this_composition</strong> – If true, substitutions with this as a final composition
will be found. If false, substitutions with this as a
starting composition will be found (these are slightly
different).</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>List of predictions in the form of dictionaries.
If to_this_composition is true, the values of the dictionary
will be from the list species. If false, the keys will be
from that list.</p>
</dd>
</dl>
</dd></dl>

</dd></dl>

<dl class="py class">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability">
<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">SubstitutionProbability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L35-L181"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>This class finds substitution probabilities given lists of atoms
to substitute. The inputs make more sense if you look through the
from_defaults static method.</p>
<p>The substitution prediction algorithm is presented in:
Hautier, G., Fischer, C., Ehrlacher, V., Jain, A., and Ceder, G. (2011)
Data Mined Ionic Substitutions for the Discovery of New Compounds.
Inorganic Chemistry, 50(2), 656-663. doi:10.1021/ic102031h</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>lambda_table</strong> – JSON table of the weight functions lambda if None,
will use the default lambda.json table</p></li>
<li><p><strong>alpha</strong> (<em>float</em>) – weight function for never observed substitutions.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.as_dict">
<span class="sig-name descname"><span class="pre">as_dict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L162-L170"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.as_dict" title="Link to this definition"></a></dt>
<dd><p>Get MSONable dict.</p>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.cond_prob">
<span class="sig-name descname"><span class="pre">cond_prob</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">s1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">s2</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L119-L132"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.cond_prob" title="Link to this definition"></a></dt>
<dd><p>Conditional probability of substituting s1 for s2.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>s1</strong> – The <em>variable</em> specie</p></li>
<li><p><strong>s2</strong> – The <em>fixed</em> specie</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Conditional probability used by structure predictor.</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.cond_prob_list">
<span class="sig-name descname"><span class="pre">cond_prob_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">l1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">l2</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L143-L160"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.cond_prob_list" title="Link to this definition"></a></dt>
<dd><p>Find the probabilities of 2 lists. These should include ALL species.
This is the probability conditional on l2.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>l1</strong> – lists of species</p></li>
<li><p><strong>l2</strong> – lists of species</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>The conditional probability (assuming these species are in
l2)</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.from_dict">
<em class="property"><span class="k"><span class="pre">classmethod</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dct</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L172-L181"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.from_dict" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>dct</strong> (<em>dict</em>) – Dict representation.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Class</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.get_lambda">
<span class="sig-name descname"><span class="pre">get_lambda</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">s1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">s2</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L88-L98"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.get_lambda" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>s1</strong> (<em>SpeciesLike</em>) – Ion in 1st structure.</p></li>
<li><p><strong>s2</strong> (<em>SpeciesLike</em>) – Ion in 2nd structure.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Lambda values</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.get_px">
<span class="sig-name descname"><span class="pre">get_px</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sp</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">SpeciesLike</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L100-L108"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.get_px" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>sp</strong> (<em>SpeciesLike</em>) – Species.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Probability</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>float</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.pair_corr">
<span class="sig-name descname"><span class="pre">pair_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">s1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">s2</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L134-L141"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.pair_corr" title="Link to this definition"></a></dt>
<dd><p>Pair correlation of two species.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>The pair correlation of 2 species</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.prob">
<span class="sig-name descname"><span class="pre">prob</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">s1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">s2</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitution_probability.py#L110-L117"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitution_probability.SubstitutionProbability.prob" title="Link to this definition"></a></dt>
<dd><p>Get the probability of 2 species substitution. Not used by the
structure predictor.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>Probability of s1 and s2 substitution.</p>
</dd>
</dl>
</dd></dl>

</dd></dl>

</section>
<section id="module-pymatgen.analysis.structure_prediction.substitutor">
<span id="pymatgen-analysis-structure-prediction-substitutor-module"></span><h2>pymatgen.analysis.structure_prediction.substitutor module<a class="headerlink" href="#module-pymatgen.analysis.structure_prediction.substitutor" title="Link to this heading"></a></h2>
<p>This module provides classes for predicting new structures from existing ones.</p>
<dl class="py class">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor">
<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Substitutor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">symprec</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L34-L265"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">MSONable</span></code></p>
<p>This object uses a data mined ionic substitution approach to propose
compounds likely to be stable. It relies on an algorithm presented in
Hautier, G., Fischer, C., Ehrlacher, V., Jain, A., and Ceder, G. (2011).
Data Mined Ionic Substitutions for the Discovery of New Compounds.
Inorganic Chemistry, 50(2), 656-663. doi:10.1021/ic102031h.</p>
<p>Use the substitution probability class to find good substitutions for a given chemistry or structure.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>threshold</strong> – probability threshold for predictions</p></li>
<li><p><strong>symprec</strong> – symmetry precision to determine if two structures
are duplicates</p></li>
<li><p><strong>kwargs</strong> – kwargs for the SubstitutionProbability object
lambda_table, alpha</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.as_dict">
<span class="sig-name descname"><span class="pre">as_dict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L243-L252"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.as_dict" title="Link to this definition"></a></dt>
<dd><p>Get MSONable dict.</p>
</dd></dl>

<dl class="py attribute">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.charge_balanced_tol">
<span class="sig-name descname"><span class="pre">charge_balanced_tol</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">float</span></em><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">1e-09</span></em><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/analysis/structure_prediction/substitutor.py"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.charge_balanced_tol" title="Link to this definition"></a></dt>
<dd></dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.from_dict">
<em class="property"><span class="k"><span class="pre">classmethod</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dct</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L254-L265"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.from_dict" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>dct</strong> (<em>dict</em>) – Dict representation.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Class</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.get_allowed_species">
<span class="sig-name descname"><span class="pre">get_allowed_species</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L67-L71"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.get_allowed_species" title="Link to this definition"></a></dt>
<dd><p>Get the species in the domain of the probability function
any other specie will not work.</p>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_comp">
<span class="sig-name descname"><span class="pre">pred_from_comp</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">composition</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">dict</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L226-L241"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_comp" title="Link to this definition"></a></dt>
<dd><p>Similar to pred_from_list except this method returns a list after
checking that compositions are charge balanced.</p>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_list">
<span class="sig-name descname"><span class="pre">pred_from_list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">species_list</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">dict</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L173-L224"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_list" title="Link to this definition"></a></dt>
<dd><p>There are an exceptionally large number of substitutions to
look at (260^n), where n is the number of species in the
list. We need a more efficient than brute force way of going
through these possibilities. The brute force method would be:</p>
<blockquote>
<div><p>output = []
for p in itertools.product(self._sp.species_list, repeat=len(species_list)):</p>
<blockquote>
<div><dl class="simple">
<dt>if self._sp.conditional_probability_list(p, species_list) &gt; self._threshold:</dt><dd><p>output.append(dict(zip(species_list, p)))</p>
</dd>
</dl>
</div></blockquote>
<p>return output</p>
</div></blockquote>
<p>Instead of that we do a branch and bound.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>species_list</strong> – list of species in the starting structure</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>list of dictionaries, each including a substitutions
dictionary, and a probability value</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_structures">
<span class="sig-name descname"><span class="pre">pred_from_structures</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target_species</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">structures</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_duplicates</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_existing</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pymatgen.alchemy.html#pymatgen.alchemy.materials.TransformedStructure" title="pymatgen.alchemy.materials.TransformedStructure"><span class="pre">TransformedStructure</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/substitutor.py#L73-L161"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.substitutor.Substitutor.pred_from_structures" title="Link to this definition"></a></dt>
<dd><p>Performs a structure prediction targeting compounds containing all of
the target_species, based on a list of structure (those structures
can for instance come from a database like the ICSD). It will return
all the structures formed by ionic substitutions with a probability
higher than the threshold.</p>
<p class="rubric">Notes</p>
<p>If the default probability model is used, input structures must
be oxidation state decorated. See AutoOxiStateDecorationTransformation</p>
<p>This method does not change the number of species in a structure. i.e
if the number of target species is 3, only input structures containing
3 species will be considered.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>target_species</strong> – a list of species with oxidation states
e.g. [Species(‘Li+’), Species(‘Ni2+’), Species(‘O-2’)]</p></li>
<li><p><strong>structures_list</strong> – list of dictionary of the form {‘structure’: Structure object, ‘id’: some id where it comes from}
The id can for instance refer to an ICSD id.</p></li>
<li><p><strong>remove_duplicates</strong> – if True, the duplicates in the predicted structures will
be removed</p></li>
<li><p><strong>remove_existing</strong> – if True, the predicted structures that already exist in the
structures_list will be removed</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>a list of TransformedStructure objects.</p>
</dd>
</dl>
</dd></dl>

</dd></dl>

</section>
<section id="module-pymatgen.analysis.structure_prediction.volume_predictor">
<span id="pymatgen-analysis-structure-prediction-volume-predictor-module"></span><h2>pymatgen.analysis.structure_prediction.volume_predictor module<a class="headerlink" href="#module-pymatgen.analysis.structure_prediction.volume_predictor" title="Link to this heading"></a></h2>
<p>Predict volumes of crystal structures.</p>
<dl class="py class">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor">
<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">DLSVolumePredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_scaling</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_scaling</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.5</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/volume_predictor.py#L132-L241"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Data-mined lattice scaling (DLS) scheme that relies on data-mined bond
lengths to predict the crystal volume of a given structure.</p>
<p>As of 2/12/19, we suggest this method be used in conjunction with
min_scaling and max_scaling to prevent instances of very large, unphysical
predicted volumes found in a small subset of structures.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>cutoff</strong> (<em>float</em>) – cutoff radius added to site radius for finding
site pairs. Necessary to increase only if your initial
structure guess is extremely bad (atoms way too far apart). In
all other instances, increasing cutoff gives same answer
but takes more time.</p></li>
<li><p><strong>min_scaling</strong> (<em>float</em>) – if not None, this will ensure that the new
volume is at least this fraction of the original (preventing
too-small volumes)</p></li>
<li><p><strong>max_scaling</strong> (<em>float</em>) – if not None, this will ensure that the new
volume is at most this fraction of the original (preventing
too-large volumes).</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor.get_predicted_structure">
<span class="sig-name descname"><span class="pre">get_predicted_structure</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><span class="pre">Structure</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">icsd_vol</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/volume_predictor.py#L228-L241"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor.get_predicted_structure" title="Link to this definition"></a></dt>
<dd><p>Given a structure, returns back the structure scaled to predicted
volume.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – structure w/unknown volume</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>a Structure object with predicted volume</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><span class="pre">Structure</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">icsd_vol</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/volume_predictor.py#L161-L226"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.volume_predictor.DLSVolumePredictor.predict" title="Link to this definition"></a></dt>
<dd><p>Given a structure, returns the predicted volume.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – a crystal structure with an unknown volume.</p></li>
<li><p><strong>icsd_vol</strong> (<em>bool</em>) – True if the input structure’s volume comes from ICSD.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>a float value of the predicted volume.</p>
</dd>
</dl>
</dd></dl>

</dd></dl>

<dl class="py class">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor">
<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">RLSVolumePredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">check_isostructural</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radii_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ionic-atomic'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_bv</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/volume_predictor.py#L23-L129"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Reference lattice scaling (RLS) scheme that predicts the volume of a
structure based on a known crystal structure.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>check_isostructural</strong> – Whether to test that the two structures are
isostructural. This algo works best for isostructural compounds.
Defaults to True.</p></li>
<li><p><strong>radii_type</strong> (<em>str</em>) – Types of radii to use. You can specify “ionic”
(only uses ionic radii), “atomic” (only uses atomic radii) or
“ionic-atomic” (uses either ionic or atomic radii, with a
preference for ionic where possible).</p></li>
<li><p><strong>use_bv</strong> (<em>bool</em>) – Whether to use BVAnalyzer to determine oxidation
states if not present.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor.get_predicted_structure">
<span class="sig-name descname"><span class="pre">get_predicted_structure</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><span class="pre">Structure</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">ref_structure</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/volume_predictor.py#L113-L129"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor.get_predicted_structure" title="Link to this definition"></a></dt>
<dd><p>Given a structure, returns back the structure scaled to predicted
volume.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – structure w/unknown volume</p></li>
<li><p><strong>ref_structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – A reference structure with a similar
structure but different species.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>a Structure object with predicted volume</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><span class="pre">Structure</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">ref_structure</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/materialsproject/pymatgen/blob/v2025.6.14/src/pymatgen/core/../analysis/structure_prediction/volume_predictor.py#L46-L111"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pymatgen.analysis.structure_prediction.volume_predictor.RLSVolumePredictor.predict" title="Link to this definition"></a></dt>
<dd><p>Given a structure, returns the predicted volume.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – structure w/unknown volume</p></li>
<li><p><strong>ref_structure</strong> (<a class="reference internal" href="pymatgen.core.html#pymatgen.core.structure.Structure" title="pymatgen.core.structure.Structure"><em>Structure</em></a>) – A reference structure with a similar
structure but different species.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>a float value of the predicted volume</p>
</dd>
</dl>
</dd></dl>

</dd></dl>

</section>
</section>


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